{
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   "source": [
    "- By: Proskurin Oleksandr\n",
    "- Email: proskurinolexandr@gmail.com\n",
    "- Reference: Advances in Financial Machine Learning, Marcos Lopez De Prado, pg 37-38"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The Single Futures Roll"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Building trading strategies on futures contracts has the unique problem that a given contract is for a short duration of time, example the 3 month contract on wheat. In order to build a continuous time series across the different contracts we stitch them together, most commonly using an auto roll or some other function. However a problem occurs when we do this, which is: come the expiry date, there is usually a price difference between the old contract and the new one. Often this difference is quite small, however for some contracts it can be quite substantial (especially if the underlying asset has a high carry costs).\n",
    " \n",
    "Consider the following example:\n",
    "September futures contract on wheat expires on December 2019, the next contract is March 2020. At the December expiration, the date at which we want to roll the contracts, the prices are:\n",
    "- December close: 100\n",
    "- March open: 120\n",
    "\n",
    "One option, which we see many people defaulting to, is to simply ignore the price difference and state the new price to be 120. A disadvantage to using this approach is if we were to train a model on this data, it will learn that every three months, around the date of expiry, prices will spike in an upward/downward fashion. It may make the wrong assumption that this is a tradeable opportunity, when in reality it isn’t. This would lead to false buy/sell signals.\n",
    "\n",
    "So what method could we apply to remedy this? The answer is the Futures Roll Trick.\n",
    "\n",
    "The book reads: \n",
    "\"The ETF trick can handle the rolls of a single futures contract, as a particular case of a 1-legged spread. However, when dealing with a single futures contract, an equivalent and more direct approach is to form a time series of cumulative roll gaps, and detract that gaps series from the price series.\" (pg 36, AFML)\n",
    "\n",
    "### Note: \n",
    "On further expirations the adjustment factor need to be accounted for as follows \n",
    "\n",
    "* Absolute returns: adjustment_factor = previous_adjustment_factor + new_roll_gap.\n",
    "* Relative returns:  adjustment_factor = previous_adjustment_factor * new_roll_gap.\n",
    "\n",
    "Let's look how Futures Roll Trick works on an example of S&P500 Emini futures contracts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import mlfinlab as ml\n",
    "\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Caveat:**\n",
    "For this notebook we made use of our inhouse data which we are not able to share due to legal constraints. We recommend you apply the same logic to your own data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "aggregated_df = pd.read_csv('../Sample-Data/volume_bars_es_with_nearest_contract.csv', index_col = 0, parse_dates = [0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>ticker</th>\n",
       "      <th>nearest_contract</th>\n",
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       "    <tr>\n",
       "      <th>date_time</th>\n",
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       "      <td>20006</td>\n",
       "      <td>ESH11</td>\n",
       "      <td>ESH11</td>\n",
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       "      <th>2011-01-03 02:47:12</th>\n",
       "      <td>1258.75</td>\n",
       "      <td>1261.5</td>\n",
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       "      <td>1260.00</td>\n",
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       "      <td>ESH11</td>\n",
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       "    <tr>\n",
       "      <th>2011-01-03 04:11:34</th>\n",
       "      <td>1260.00</td>\n",
       "      <td>1261.0</td>\n",
       "      <td>1259.00</td>\n",
       "      <td>1260.50</td>\n",
       "      <td>20146</td>\n",
       "      <td>ESH11</td>\n",
       "      <td>ESH11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-03 06:01:23</th>\n",
       "      <td>1260.50</td>\n",
       "      <td>1261.5</td>\n",
       "      <td>1260.50</td>\n",
       "      <td>1260.50</td>\n",
       "      <td>20005</td>\n",
       "      <td>ESH11</td>\n",
       "      <td>ESH11</td>\n",
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      "text/plain": [
       "                        open    high      low    close  volume ticker  \\\n",
       "date_time                                                               \n",
       "2011-01-02 21:50:39  1256.00  1261.0  1255.25  1260.00   20015  ESH11   \n",
       "2011-01-03 02:00:37  1260.00  1261.5  1258.50  1258.75   20006  ESH11   \n",
       "2011-01-03 02:47:12  1258.75  1261.5  1258.50  1260.00   20040  ESH11   \n",
       "2011-01-03 04:11:34  1260.00  1261.0  1259.00  1260.50   20146  ESH11   \n",
       "2011-01-03 06:01:23  1260.50  1261.5  1260.50  1260.50   20005  ESH11   \n",
       "\n",
       "                    nearest_contract  \n",
       "date_time                             \n",
       "2011-01-02 21:50:39            ESH11  \n",
       "2011-01-03 02:00:37            ESH11  \n",
       "2011-01-03 02:47:12            ESH11  \n",
       "2011-01-03 04:11:34            ESH11  \n",
       "2011-01-03 06:01:23            ESH11  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aggregated_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>ticker</th>\n",
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       "      <th>2017-12-29 15:14:27.864</th>\n",
       "      <td>2672.50</td>\n",
       "      <td>2673.5</td>\n",
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       "                            open    high      low    close  volume ticker  \\\n",
       "date_time                                                                   \n",
       "2017-12-29 15:14:27.864  2672.50  2673.5  2671.75  2673.25   20011  ESH18   \n",
       "2017-12-29 15:57:21.199  2673.25  2673.5  2668.00  2668.25   20167  ESH18   \n",
       "\n",
       "                        nearest_contract  \n",
       "date_time                                 \n",
       "2017-12-29 15:14:27.864            ESH18  \n",
       "2017-12-29 15:57:21.199            ESH18  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aggregated_df.tail(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Continuous Contracts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get roll gaps (absolute and relative)\n",
    "roll_gaps_absolute = ml.multi_product.get_futures_roll_series(aggregated_df, open_col='open', close_col='close',\n",
    "                                                   sec_col='ticker', current_sec_col='nearest_contract', method='absolute')\n",
    "\n",
    "roll_gaps_relative = ml.multi_product.get_futures_roll_series(aggregated_df, open_col='open', close_col='close',\n",
    "                                                   sec_col='ticker', current_sec_col='nearest_contract', method='relative')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <th>volume</th>\n",
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       "      <td>1258.75</td>\n",
       "      <td>20006</td>\n",
       "      <td>ESH11</td>\n",
       "      <td>ESH11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-03 02:47:12</th>\n",
       "      <td>1258.75</td>\n",
       "      <td>1261.5</td>\n",
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       "      <td>1260.00</td>\n",
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       "      <td>ESH11</td>\n",
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       "    <tr>\n",
       "      <th>2011-01-03 04:11:34</th>\n",
       "      <td>1260.00</td>\n",
       "      <td>1261.0</td>\n",
       "      <td>1259.00</td>\n",
       "      <td>1260.50</td>\n",
       "      <td>20146</td>\n",
       "      <td>ESH11</td>\n",
       "      <td>ESH11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-03 06:01:23</th>\n",
       "      <td>1260.50</td>\n",
       "      <td>1261.5</td>\n",
       "      <td>1260.50</td>\n",
       "      <td>1260.50</td>\n",
       "      <td>20005</td>\n",
       "      <td>ESH11</td>\n",
       "      <td>ESH11</td>\n",
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      ],
      "text/plain": [
       "                        open    high      low    close  volume ticker  \\\n",
       "date_time                                                               \n",
       "2011-01-02 21:50:39  1256.00  1261.0  1255.25  1260.00   20015  ESH11   \n",
       "2011-01-03 02:00:37  1260.00  1261.5  1258.50  1258.75   20006  ESH11   \n",
       "2011-01-03 02:47:12  1258.75  1261.5  1258.50  1260.00   20040  ESH11   \n",
       "2011-01-03 04:11:34  1260.00  1261.0  1259.00  1260.50   20146  ESH11   \n",
       "2011-01-03 06:01:23  1260.50  1261.5  1260.50  1260.50   20005  ESH11   \n",
       "\n",
       "                    nearest_contract  \n",
       "date_time                             \n",
       "2011-01-02 21:50:39            ESH11  \n",
       "2011-01-03 02:00:37            ESH11  \n",
       "2011-01-03 02:47:12            ESH11  \n",
       "2011-01-03 04:11:34            ESH11  \n",
       "2011-01-03 06:01:23            ESH11  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter out rows where there is a roll (a change in nearest contract)\n",
    "# This forms the basis of the continuous contract\n",
    "continuous_contract = aggregated_df[aggregated_df.ticker == aggregated_df.nearest_contract]\n",
    "continuous_contract.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Subtract or divide the gaps from close prices. This depends on if you are using the absolute or relative method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make a copy of the first contract\n",
    "continuous_contract_absolute_method = continuous_contract.copy()\n",
    "continuous_contract_relative_method = continuous_contract.copy()\n",
    "\n",
    "# Apply the roll gaps\n",
    "continuous_contract_absolute_method['close'] -= roll_gaps_absolute\n",
    "continuous_contract_relative_method['close'] /= roll_gaps_relative"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot nearest continuous futures contract the using different fill methods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot\n",
    "plt.figure(figsize=(20, 10))\n",
    "continuous_contract.close.plot(label = 'Autoroll Series')\n",
    "continuous_contract_absolute_method.close.plot(label = 'Absolute Return Roll')\n",
    "continuous_contract_relative_method.close.plot(label = 'Relative Return Roll')\n",
    "plt.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "As you can see, accounting for the differences in contract prices can be quite substantial, by not accounting for it you add additional noise to the model.\n",
    "\n",
    "\n",
    "### Notes from the book:\n",
    "\"Rolled prices are used for simulating PnL and portfolio mark-to-market values. However, raw prices should still be used to size positions and determine capital consumption. Keep in mind, rolled prices can indeed become negative, particularly in futures contracts that sold off while in contango.\" (pg 37, AFML)"
   ]
  }
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